Agricultural Transformation in Nepal: An Econometric Analysis
DOI:
https://doi.org/10.3126/panauti.v3i01.83979Keywords:
agricultural transformation, Pooled OLS, Ridge, Lasso, Elastic Net RegressionsAbstract
Agricultural transformation in Nepal, reflecting changes in productivity, structure, and economic contribution, is influenced by various socioeconomic and demographic factors. This study examines how these factors influence agricultural value added (% of GDP) in the country. For this purpose, data from two sources—the World Bank and the World Population Prospects 2024—were used, in which an econometric analysis approach was applied to assess the level of agricultural transformation in Nepal. While the overall relationship was statistically significant, the individual effects of the independent variables were too trivial to establish meaningful interactions. To address this issue, econometrics of three additional regression techniques—Ridge, Lasso, and Elastic Net—were employed to better identify the true contributions of the independent variables to the dependent variable. Key variables such as sex ratio, population growth rate, agriculture-related imports and exports, urban population, remittances, and per capita gross national income emerged as the most relevant factors in explaining variations in agriculture value added. The findings imply that targeted policies addressing demographic, economic, and trade-related factors are essential to effectively enhance agricultural value added and support Nepal’s agricultural transformation.
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